Freesurfer June 2019

freesurfer@nmr.mgh.harvard.edu

82 participants
138 discussions

spatial scale bar question
by Nasiriavanaki, Zahra 16 Aug '19

16 Aug '19

Dear Freesurfers Hi I am trying to add a spatial scale bar to my cortical maps in tksurfer. However, as it's mentioned in Freesurfer forum before, the scale bar in tksurfer shrinks when you zoom in the brain. I couldn't find a scale bar option in Freeview neither. I appreciate if you could let me know how to get a scale bar. Thanks Mona

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voxel coordinates of corpus collosum
by Sadia Sheikh 18 Jul '19

18 Jul '19

External Email - Use Caution Dear Freesurfer experts How can I get the voxel coordinates of the segmented corpus callosum? I tried using the command mri_vol2label and id of the corpus callosum as 192 as given in Freesurfer LUT, but it gives an error: found no voxels matching id 192 Thanks in advance Sadia

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recon-all error: Correcting defect
by Miguel Ángel Rivas Fernández 08 Jul '19

08 Jul '19

External Email - Use Caution I ran the recon-all in one subject and and this process was stopped in the topology correction. In particular during the "CORRECTING DEFECT 36 (vertices=19847, convex hull=5892, v0=94733)". I reviewed the lh.inflated.nofix and the lh.orig.nofix files in Freeview and I noticed that the this error would be located in the lh.inflated.nofix file. I am not completely sure but I suspect that this error may be due to the fact that there is a large amount of brain lesion and this would difficult the topology correction. How can I fix this problem? Thanks in advance. Best regards, -- *Miguel Ángel Rivas Fernández*

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"MATLAB: Undefined variable" error, FSFAST Tutorial, using Octave
by Zacharie Saint-Georges 02 Jul '19

02 Jul '19

External Email - Use Caution Dear Freesurfer Developers, I am running into a "MATLAB: Undefined variable" error while doing the FSFAST tutorial, using Ubuntu 18.04, Freesurfer v6, and Octave***. I did try a few solutions posted already (please see links below), but I still cannot successfully run the tutorial command line. .basrc additions for Octave environment variables (Ref: https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg21241.html) export FS_OCTAVE_LIB=/usr/bin/octave export FS_OCTAVE_LIB=/usr/bin/octave additional command line: export FS_USE_OCTAVE=1 Ref: https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg60448.html main command line: mkcontrast-sess -analysis my-workmem.sm05.lh -contrast encode-v-base -a 1 (tutorial page: https://surfer.nmr.mgh.harvard.edu/fswiki/FsFastTutorialV6.0/FsFastFirstLev… ) error output: INFO: Found 5 Non-Null Conditions INFO: Found 1 Delays Condition Weights: 1.00000000000000000000 0 0 0 0 mkcontrast2 -config my-workmem.sm05.lh/encode-v-base.config -anadir my-workmem.sm05.lh -wcond 1.00000000000000000000 0 0 0 0 -sumconds -o my-workmem.sm05.lh/encode-v-base.mat -wdelay 1 -octave $Id: mkcontrast2,v 1.3 2016/03/11 23:46:48 greve Exp $ cmtxfile my-workmem.sm05.lh/encode-v-base.mat nconds 5, wcond 1.00000000000000000000 0 0 0 0 ndelays 1, wdelay 1 ndelays 1, wpsa sumconds 1 sumdelays 0 nircorr 0 TER 0.050000 rdelta rtau cmtxfile my-workmem.sm05.lh/encode-v-base.mat monly 0 NCond 5 WCond 1.00000000000000000000 0 0 0 0 NDelay 1 WDelay 1 TER 0.050000 sumconds 1 sumdelays 0 nircorr 0 TPreStim 0 RmPreStim 0 rdelta 0 0 rtau 0 0 ndelays 1 CNorm 1 setwdelay 0 setwcond 0 Matlab file is /tmp/mkcontrast2.18977.m MATLAB: Undefined variable. ERROR running mkcontrast mkcontrast2 -config my-workmem.sm05.lh/encode-v-base.config -anadir my-workmem.sm05.lh -wcond 1.00000000000000000000 0 0 0 0 -sumconds -o my-workmem.sm05.lh/encode-v-base.mat -wdelay 1 -octave Tue May 28 16:51:41 EDT 2019 I also modified the mkcontrast freesurfer file according to this post: Ref: https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg58758.html Thank you for your assistance! Regards, Zach Zacharie Saint-Georges Research Assistant Royal Ottawa Institute for Mental Health Research Zacharie.Saint-Georges(a)TheRoyal.ca

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Freesurfer linear mixed models - viewing results
by Mark Wagshul 02 Jul '19

02 Jul '19

External Email - Use Caution Dear FreeSurfer users/experts, I am working on a mass-univariate linear mixed effects model with cortical thickness data, with multiple time points, a cognitive measure as our primary independent variable and the usual covariates (age, gender, etc). Subject is treated as a random variable (i.e. the first column of all ones is the random variable "Zcols"). We have run through the first few steps to produce the covariance matrices, and note a number of clusters of significance using the "patch" function with the results projected onto lhsphere. We would like to view these results in a more conventional manner, e.g. projected onto the inflated cortex of fsaverage. Is this possible? Thanks for any advice you can provide. Best, Mark ____________________ Mark Wagshul, PhD Associate Professor Gruss Magnetic Resonance Research Center Albert Einstein College of Medicine Bronx, NY 10461 Ph: 718-430-4011 FAX: 718-430-3399 Email: mark.wagshul(a)einstein.yu.edu<mailto:mark.wagshul@einstein.yu.edu> [einstein-logo-rgb] This email message and any accompanying attachments may contain privileged information intended only for the named recipient(s). If you are not the intended recipient(s), you are hereby notified that the dissemination, distribution, and or copying of this message is strictly prohibited. If you receive this message in error, or are not the named recipient(s), please notify the sender at the email address above, delete this email from your computer, and destroy any copies in any form immediately.

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[DEADLINE EXTENSION]: The 2nd International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2019): ENTERING THE ERA OF BIG DATA VIA TRANSFER LEARNING AND DATA HARMONIZATION
by MLCN Workshop 30 Jun '19

30 Jun '19

External Email - Use Caution Dear Colleagues,The submission deadline for MLCN 2019 workshop as a satellite event of the MICCAI 2019 conference has been extended to 14/07/2019. For more information, please visit https://mlcnws.com/call-for-papers/ . Call for Papers Recent advances in neuroimaging and machine learning provide an exceptional opportunity for investigators and physicians to discover complex relationships between brain, behaviors, and mental and neurological disorders. The MLCN 2019 workshop (https://mlcnws.com) as a satellite event of MICCAI 2019 (https://www.miccai2019.org) aims to bring together researchers in both theory and application from various fields in domains such as *e.g.* machine learning, neuroimaging, predictive clinical neuroscience, *etc.* Topics of interests include, but are not limited to: - Transfer learning in clinical neuroimaging - Model stability in transfer learning - Data prerequisites for successful transfer learning - Domain adaptation in neuroimaging - Data harmonization across sites - Data pooling – practical issues - Cross-domain learning in neuroimaging - Interpretability for transfer learning - Unsupervised methods for domain adaptation - Multi-site data analysis, from preprocessing to modeling - Big data in clinical neuroimaging - Scalable machine learning methods - Benefits, problems, and solutions of working with very large datasets SUBMISSION PROCESS: The workshop seeks high quality, original, and unpublished work on algorithms, theory, and applications of machine learning in clinical neuroimaging related to big data, transfer learning, and data harmonization. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style ( https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…) with up to 8-pages and using the CMT system at https://cmt3.research.microsoft.com/MLCN2019. The MLCN workshop uses a double-blind review process in the evaluation phase, thus authors must ensure anonymous submissions. Accepted papers will be published in a joint proceeding with the MICCAI 2019 conference. IMPORTANT DATES: - Paper submission deadline: July 14, 2019 (23:59 PST) - Notification of Acceptance: August 5, 2019 - Camera-ready Submission: August 12, 2019 - Workshop Date: October 13, 2019 Best regards, MLCN 2019 Organizing Committee <https://mlcnws.com/organization/>, Email: mlcnworkshop(a)gmail.com Website: https://mlcnws.com/ twitter: @MLCNworkshop <https://twitter.com/MLCNworkshop>

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Re: [Freesurfer] Longitudinal Masking and FDR
by Hua, Jessica 29 Jun '19

29 Jun '19

External Email - Use Caution Hi Kersten, I used this code to calculate the threshold: P = [ F_lhstats1.pval(lhcortex) F_rhstats1.pval(rhcortex) ]; G = [ F_lhstats1.sgn(lhcortex) F_rhstats1.sgn(rhcortex) ]; [detvtx,sided_pval,pth] = lme_mass_FDR2(P,G,[],0.05,0); pcor = -log10(pth) I substituted 0.1, 0.2, 0.5, 0.8, and 1 where the 0.05 is, and I kept getting the same pcor value of 4.8943. Jessica Hua

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mis-registartion question
by Nasiriavanaki, Zahra 28 Jun '19

28 Jun '19

Dear Freesurfers Hi I checked the functional to anatomical data registration using tkregister-sess -s $subj -fsd bold -per-run -bbr-sum. (The functional data is only collected from parietal and occipital lobes in 7T scanner). The values obtained from tkregister-sess are too high (0.95) for 7 out of 8 runs. When I looked at the snapshots obtained from QA_tools, they looked ok (top row images). But, when I looked at the volumes of the individual runs using tkregister2 command, the registration doesn't look good (bottom row images). tkregister2 --s $subj --mov /$subj/bold/011/template.nii.gz --surf --reg new.dat --regheader . I'm wondering if I need to do manual edits, and I appreciate any advice on that. Thanks Mona [cid:91ee52eb-c146-4bee-8cc8-19bf01ef7547][cid:487a26fa-1c27-4ed5-bd48-26a587d477d7] [cid:479ab0d3-00f7-406c-886c-4d83c945708e][cid:332d78df-9a82-4c35-a603-aa7a1734ba0f] Zahra (Mona) Nasiriavanaki Postdoctoral Research Fellow Martinos Center for Biomedical Imaging Massachusetts General Hospital 149 13th Street, 149-2615 Charlestown, MA, USA, 02129

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total cortical area
by Barletta, Valeria 28 Jun '19

28 Jun '19

Dear Freesurfers, Where in the /mri/stats folder can I find the total cortical surface in mm2? Is it in the ?h.aparc.stats or in the ?h.curv.stats? Thank you, Valeria

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How to account for gender in a contrast matrix
by Basavaraju, Rakshathi 28 Jun '19

28 Jun '19

External Email - Use Caution Dear all FS users, I wanted to know the way of accounting for gender in a simple regression analysis of cortical thickness against 2 continuous variables. Th example of contrast matrix given in the downloaded tutorial data for cortical thickness with age without accounting for gender is, 0 0 0.5 0.5 . However if we want to factor in gender how do we do it? Is it 0.5 0.5 0.5 0.5? or something else? Answers regarding same will be very much appreciated. Thanks, Dr. Rakshathi Basavaraju (MD Psychiatry) Postdoctoral Research Scientist Taub Institute Columbia University Irving Medical Centre 622 West, 168th Street, New York - 10032 E-Mail: rb3419(a)cumc.columbia.edu<mailto:rb3419@cumc.columbia.edu> http://www.wellcomedbt.org/fellowsprofile/dr-rakshathi-basavaraju-288

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Freesurfer June 2019